This project focuses on detecting spam reviews on movie platforms like IMDb by classifying reviews into truthful, untruthful, or brand-only categories. The system removes duplicate reviews and analyzes attributes such as review questions, product comparisons, rating inconsistencies, and reviewer behavior. Key modules include review extraction, parsing, preprocessing, and classification. The classifier uses various features like extreme ratings, helpful feedback, and time intervals between reviews to determine the authenticity of the review. The system helps identify fake reviews, enhancing trust in online movie reviews.